The search for novel risk factors and genetic modifiers for Alzheimer disease relies on the access to accurate and deeply phenotyped datasets. The Memory and Aging Project (MAP) at the Knight-ADRC (Washington University in St. Louis) collects cognitive data, CSF and imaging longitudinally.  This clinical information combined with deep molecular phenotyping (i.e. genetic, proteomics, transcriptomics, metabolomics and lipidomics among others) will lead to the identification of novel genetic modifiers, protective variants, molecular biomarkers and the novel targets. Participants were recruited by the Knight-ADRC at Washington University in St. Louis (MO). Knight-ADRC participants have to be at least 65 years old and have no memory problems or mild dementia at the time of enrollment.

The cohort consists of individuals who are non-Hispanic white from North America (95%) or African American (5%). Individuals carrying known mutations in the Mendelian genes for AD (APP, PSEN1, PSEN2) or Frontotemporal Dementia (GRN, MAPT, C9ORF72) were excluded.  AD definition is based on a combination of both clinical and pathological information if available. Pathologic diagnosis will overrule clinical diagnosis.  Autopsy information is provided if available, but is not a requirement for enrollment.

Knight ADRC Datasets Available in DSS

The datasets listed here are available for request through NIAGADS DSS.

Accession NumberDataset NameData TypeSamples/SubjectsLast Release Date
NG00067NG00067 – ADSP UmbrellaAnnotationHarmonized PhenotypesStructural Variant CallsWhole Exome SequencingWhole Genome Sequencing110,270November 27, 2024
NG00102NG00102 – Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disordersProteomic/MetabolomicQTL Summary Statistics1,157November 7, 2023
NG00108NG00108 – Profiling microglia expression profiles in AD using single-nuclei RNA-seqSingle Cell RNA Sequencing44November 23, 2021
NG00113NG00113 – Metabolomic and lipidomic signatures in Alzheimer disease brainsProteomic/Metabolomic423February 4, 2022
NG00114NG00114 – DNA Methylation in Alzheimer disease brainsMethylation413February 4, 2022
NG00127NG00127 – A longitudinal study of Alzheimer Disease and other dementing illnesses – KnightADRC GWASGenotyping SNP Array4,496December 13, 2022
NG00128NG00128 – Proteomic profiling identified plasma biomarkers for SARS-CoV-2 infection and severity of COVID-19 patientsProteomic/Metabolomic482January 18, 2023
NG00130NG00130 – Large scale CSF proteogenomic atlasQTL Summary Statistics0July 27, 2023
NG00131NG00131 – Large scale genetics study on CSF and brain metabolite levelsQTL Summary Statistics0August 10, 2023

Knight ADRC Datasets Available in Archive NIAGADS

The datasets listed here are currently available for request through the NIAGADS archive website. All datasets are in the process of being moved over to DSS.

DatasetNameTypeCases/ControlsTotal Subjects
NG00030WashU1 GWASGWAS
Imputation
208 / 350678
NG00035GWAS of CSF tau levels identifies risk variants for ADGWAS
Imputation
NA1934
NG00049CSF Summary Statistics- Cruchaga et al. (2013)Summary StatisticsNANA
NG00050GWAS of CLU, A potential endophenotype for Alzheimer’s diseaseGWAS
Imputation
NA673
NG00051SORL1 coding variants and risk for ADTargeted Genotyping
Targeted Sequencing
sEOAD- 212/167
sLOAD- 134/266
fLOAD- 866/324
sEOAD- 379
sLOAD- 400
fLOAD- 1190
NG00052CLU, A potential endophenotype for AD: Summary Statistics- Deming et al. (2016)Summary StatisticsNANA
NG00055CSF Aβ/ptau Summary Statistics – Deming Y et al. (2017)Summary StatisticsNANA
NG00083Circular RNAs in Alzheimer Disease Brains – RNA-seq DataSummary Statistics/RNA-SeqNANA
NG00085ExomeChip – WashUGWAS519 / 349868
NG00087WashU2 GWASGWAS
Imputation
38 / 94235
NG00089CSF TREM2 Summary StatisticsSummary StatisticsNANA

This work was supported by grants from the National Institutes of Health (R01AG044546, P01AG003991, RF1AG053303, R01AG058501, U01AG058922, RF1AG058501 and R01AG057777). The recruitment and clinical characterization of research participants at Washington University were supported by NIH P50 AG05681, P01 AG03991, and P01 AG026276. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, and the Departments of Neurology and Psychiatry at Washington University School of Medicine. We thank the contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible.